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Land Use Change - Science topic

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If possible How Ecological restoration could be related to Climate Change OR Land Use Change ?
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Maybe you can try coral reef restoration if you're interested in marine ecology:
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Hello everyone,
I am doing LULC of the arid region, I have acquired landsate 8 image data from USGS website and I have done preprocess in qgis using semi-automatic classification plugin using the standard tutorial and I have converted by DN into reflections value for LULC. however, I facing difficulties in assigning classes for built-up area and bare soil as they have high overlap spectral values.
besides this, I have also used SAVI as well as Modified bare soil index though it's not helping in my problem.
Anyone can tell me what to do in that case.
Thank you.
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Kory Postma thank you very much for your response.
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Are there any examples of good practices and new paradigms that you come across when considering agricultural land use (especially the measures taken by developing countries)?
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Yaseen A Al-Janabi What I meant by agricultural land use was somewhat different, but thanks for your comment anyway and I agree with your point about the introduction of contemporary irrigation systems. Because land and water management practices specifically start in the field not outside of it.
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Can somebody please provide links to papers consisting of tables with maximum canopy storage values against corresponding landuses? Classification of landuse as used by ESRI is preferrable.
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Hope you get some idea from the following paper
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Dear Experts,
What is the best method and resource to create a detailed landcover map of an urban area?
i need these classes: green space, water-body, farmland, bare land, building, and road
I need the land cover maps of 2000, 2005, 2010, 2015, and 2020.
Thank you
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Dear Majid,
You may use Landsat satellites to cover these years. You may also increase the spatial resolution to 15 meters using pan sharping technique. About the classes, many methods can be applied whether supervised or non. It depends in the analysis and purposes. Envi and Erdas are good choices to apply that.
Best wishes,
Jasem
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I have tried to give input LULC maps into the model of a sub-basin with irregular boundary. I have faced an issue with no-data pixels. But, when I gave a regular rectangular boundary, there was smooth processing. My question is, Is it mandatory to use a rectangular bounding box for LULC input maps for future prediction models?
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Yes indeed.
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Oscar Borsato and I are organizing a free web platform “Urban Policies” where we can discuss by virtual communications of the following topics:
1) Ecologically-Compatible Urban Planning
2) Land Use Changes
3) Modelling Ecosystem Services for sustainable urban planning
We can organize Theoretical, Practical GIS, or Case of Study dicussions.
If you are interested, please let us know (writing at urbanpolicies.eu@gmail.com or wia WTZ at +39 349 64 26 511) whether we can keep your contact to organize the first online course.
We will create a mailing list and contact of interested researchers.
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I am interested!
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I have to implement Green Ampt Infiltration equation for daily time step with regional scale over different Land use/Land cover conditions. The Green Ampt parameters are estimated using soil properties, how the equation could be improved for different LULC conditions and what could be the effect of varying spatial and temporal resolution in model performance.
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That is a good question.
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I face a problem in LULC classification, like as an industrial area showing as a water body.
Please help me.
Thank you.
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band 4, 5, 6 is the best three-band combination and band 1, 2, 5, 7 is the best four-band combination which achieved almost identical performance as using all bands for LULC classification.
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We want to prepare village level crop maps (based on the land use maps) using Google Earth Engine and machine learning algorithm. There are around 27 major crops in Maharashtra.
  1. Can there be as many as 27 classes in the classification?
  2. On what basis can we decide the maximum number of classes algorithm can support?
  3. What is the optimum number of classes to achieve maximum accuracy?
  4. What is the number of ground truth points required for each class? What sample size is good sample size?
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Thanks for the question. The answers also interest me
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Hello,
Can someone recommend a model (preferably not too input demanding) that simulates climate change and/or land use-change scenario using Ecosystem services as output (e.g., soil c stock, primary production, landscape aesthetic value, ...)
Thank you
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Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) models have been widely applied to map and quantify ecosystem services and their changes. InVEST is a spatially explicit tool including a suite of open-source software models.
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Respected sir/mam,
I want to simulate the urban expansion using different time series LULC based on satellite image. please suggest me most suitable model for urban simulation.
Thanks and regards.
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I am working on the master plan for a small city in Iran. I have faced a paradoxical situation!
The city is surrounded by green spaces (specifically the garden city or second house spaces). We don't know how to deal with these spaces. If we add them to the formal boundary of the city, they would be the case for converting to housing and other urban land uses. If we put it out of the formal boundary, there would be no control over the transformations.
I would be happy to hear your perspectives on this issue.
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You must see what are the upper and lower issues in the planning system and how they have linked and intertwisted and find the gaps. Sometimes these gaps are regulative and technical. However, in the global south countries, we do not have strong regulative support and always third parties involve to take over the resources in the name of any kind of development. Furthermore, you might need to look at transnational policies and guidelines and how the national and sub-national decision-makers work with them. This is what in geography we call place-space and how specific resource (might be kind of green development) is favorable for the national and international market.
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I am seeking the best current methods and datasets (highest possible resolution) for defining and assessing global land degradation - ideally with a time series. I know there are different ways of exploring this e.g. biomass, productivity, land use/cover etc., but I would appreciate any thoughts on current modelling, datasets/resources and novel approaches.
I am also interested in the best methods for quantitatively mapping/modelling land restoration (biophysical) on a global scale, and if possible, historic land reconstruction.
Thanks!
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Hi Jake,
It is a daunting task and not very easy to answer. We have been struggling with it for a while now. From our experiences it comes back to two basic challenges. The first one is how you define land degradation (see our recent publication below), but of course also to obtain the proper datasets. In our research we are focusing on creating a time series of a range of soil properties. We are currently aiming to at a time series of soil conditions for the UN statistics division in the context of their national accounting.
Cheers Jetse
Sterk, G., Stoorvogel, J.J., 2020. Desertification–Scientific Versus Political Realities. Land 2020, 9, 156; doi:10.3390/land9060156.
Stoorvogel, J.J., Bakkenes, M., ten Brink, B.J.E., and Temme, A.J.A.M., 2017. To what extent did we change our soils? A global comparison of natural and current conditions.. Land Degrad. Develop., doi: 10.1002/ldr.2721.
Stoorvogel, J. J., Bakkenes, M., Temme, A.J.A.M., Batjes, N.H., and ten Brink, B.J.E., 2017. S-World: A Global Soil Map for Environmental Modelling. Land Degrad. Develop., 28: 22–33. doi: 10.1002/ldr.2656.
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I have already been read many articles and found some methods but those are not cleared to me.
Can you please suggest me how to generate different LST map of each land classes using ArcGIS?
Or if you have any other methods to generate the LST of each land class please do recommend?
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@Pir Mohammad
I will try. Thank you so much for your valuable comments and suggestions.
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Respected sir/mam,
I have using satellite image of Landsat 8 and 5 for LULC classification. I am confused that which software and method are the best for LULC classification?
Please help me.
Thanks and Regards
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Most GIS and RS software have the standard classification methods (ArcGIS, QGIS, ENVI, Eedas etc).
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I'm looking for a standard model to quantify the land change drivers (e.g., forest to agriculture or vs). Actually, it depends on the data that I have and the specific location, but I would like to have a good review of what has been done on this topic.
Thank you.
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Considerable land changes have been recorded periodically world over. Dynamics and spatial determinants of land change could be achieved through integration of decadal (10 year gap) cover maps. Landsat images covering spatiotemporal socioeconomic database need be reinforced with collective evidence (ground truth). They are covered under Land Use and Land Cover Change (LULCC)
Land change is a result of cropland (fallow) conversion and forest area changes excluding commercial plantations. Crop land to fallow conversions occur due to many reasons – lack of irrigation facilities, capital investment, labour shortage or even fragmentation of land holdings.
Similarly, substantial gross forest loss happens due to mainly developmental activities and to some extent conversion to crop land although there are some efforts on forest cover regeneration and supplement of degraded forests.
Comparative figures for Human land use (world-55%; India-83%); Climate change (world-20-24%; India 25-30%) and Land degradation (world-8-41%; India -57%) are some examples. However, the land classification includes many more classes as well.
What is important however is to strategies and reduce Loss:gain ratio with the data compiled over a period with judicious planning.
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This figure is about "Percentage change in land use land cover classes over Africa 2000–2015."
It is collected from a paper titled "Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing"
Can anyone suggest link of any supplementary script relevant to this?
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Is there a specific reagion you need to generate a land use change chart?
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I am doing wrf simulation to study is there any impact of LULC on extreme precipitation. So I need to use Bhuvan's latest LULC data.
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So, first you need to match/convert your Bhuvan's AWiFS LULC data classes into 24 classes of USGS classification. You can find the classes in the WRF user guide in the Chapter 3.
After the translation, you will have your data in the correct classification to insert in WRF. Now you need to convert the TIFF file (I am expecting you LULC data is a raster file) into binary format (BIL) required by WRF.
I usually use the convert_geotiff function from openWRF, which you ca find at https://github.com/openwfm/convert_geotiff
This tool will convert the tiff into binary and also will create the index file. This index file holds the information of your data, like resolution, description, extension, etc. (take a look in the other LULC in the geog folder).
After the conversion in binary format, move this files to a folder inside the geog data location (take care to not override the WRF default data)
The next step is to edit the GEOGRID.TBL file inside the WPS folder.
The GEOGRID.TBL holds the information of all land surface data to WPS/WRF, so you just need to edit the Land use section of the file, add one "name" to your data, set the interpolation method, and set the path to your data/folder.
This will helps WPS to find your data and how to proceed with it.
Next step is to edit your namelist.wps.
When you look at it, you will see the geog path is set to default.
for example, a wrf configuration of two domains, you will see something like this:
geog_data_res = 'default','default'
you just need to edit this line into
geog_data_res = 'name_you_set_in_TBL + default', ' name_you_set_in_TBL + default'
So, WPS will look first at the "name_you_set_in_TBL" data, and extract the LULC data to your domain. After extract your data, WPS will look at the default data to extract the other parameter to WRF
The chapter 3 of the user guide also helps you to set this variables, edit the GEOGRID.TBL, and namelis.wps.
Regards
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I do not have enough funding to purchase software specifically designed for image processing like ENVI and ERDAS Imagine. Alternatively I am seeking a way to make use my ArcMap 10.1, even though I never tried using this for atmospheric correction.
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conversion of digital number to reflectance can be done in ArcGIS.
The steps involved in this process:
Geodata ----> Data types ----> Rasters and Images -----> Processing and analyzing raster data ------> Apparent reflectance function
The process is applicable to sensors like Landsat, IKONOS, and QuickBird.
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We live in a changing world. Not only the climate is changing but also the system that is exposed to this climate.
In the discussion on the impacts of climate change, the changing climate is given a very important role, while non-climatic factors (e.g. land use, demographic/socio-economic factors) are often only the subject of studies of the status quo. However, the changes or transformation of such non-climatic factors in the future are often not adequately considered.
Aren't these factors equally or even more important, as there is a large scope for action, especially in the distribution of these elements?
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Different transportation, land-use, environmental, and other corresponding planners propose their work for new city urban plans in order to address the existing problems by identifying the major gaps they had. The existing land-use was following bad planning principles and it is already a failed plan. When planners integrate their proposed spatial plan to existing land use, they will have a real challenge in aligning. So, as a planner, what would be your choice to align the proposal you have with the existing land-use?
  1. Shall i follow the standard plan i have and remove the existing unplanned land-uses( NB: the compensation cost may be too large) ? or
  2. Shall i accept the existing situation as it is and compromise the planning standards?
What is your suggestion?
Any help is appreciated very much.
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From a southern perspective, I will go for option 2. Like @Luis Fernando indicated, we need to rethink our understanding of city making especially in the global south. Obviously the city is being shaped largely by the people as opposed to 'our plans' - let's plan from the peoples perspective (inclusive, participatory planning). Miraftab's piece on 'insurgent planning' will offer you a clearer insight of my point of departure. Hope this helps
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I am trying to make LULC of an area to access temporal changes using Landsat imageries of TM and OLI sensors. The problem is that the bare area, sand in river body, and built-up area appear same. So, are there any specific indices or speciality of any band that can be used to differentiate these LULC classes?
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40 seconds ago
Try arcMap it have many indicators to separate land us, you need someone have expereince in this programme..
Regards@
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Dear experts, I badly need a help to solve the problem of Landsat image classification of a coastal region of Bangladesh. The problem is regarding supervised classification of a coastal district. The land cover spectral reflectance value of pixels is quite complex. The Pixel values of Build up area and Barren land are very close. When selecting the Training sample pixels for Urban area and Barren lands that are often in conflict in the output. There are many unwanted areas in the classified image. Like many unwanted buildup areas or many Barren lands occupy Buildup areas. I tried more and less training inputs for urban area several times. but the results are not appropriate. Can you please suggest any ways to solve the problem??
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Hi Sarowar,
A good strategy is to run a parallel unsupervised classification and check out the spectral signatures of your training samples. This can inform you about the spectral differences/similarities between your expert classes. You can use this information to split your 'barren lands' and/or 'buildup' into multiple classes. Having more classes might improve the strength of the classification and you can always regroup the classes afterwards.
Regards,
Maarten
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It all started with the Normalized Difference Vegetation Index (NDVI). I am curious to know how a researcher gets to derive or modify such mathematical (sometimes complicated equations) equations by making use of two bands (absorbing and reflecting bands)? Is it by trial and error method?
For example, NDVI seems to be a simple normalization of NIR and RED bands. MSAVI has NIR and red bands along with mathematical operations both in numerator and denominator. How do we come to such a relatively complex formula?
Thank you very much in advance.
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The modified vegetation indices (such as EVI and MSAVI) are generally aimed to reduce the effects of atmosheric attenuation and soil background. The form of these complex formula can be determined or inspired by radiative transfer theory and also soil line theory. The coefficients are determined empirically or based on training datasets.
Trial and error method can be used to develop new indices, but the new indices should in most cases be supported by physical principles. Even for the machine learning method, those important independent variables (related to the dependent variable) are generally selected for learning.
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Hello,
I want to predict land-use changes for the distant future (like 2050 or beyond). my data collection is for 1995-2005-2015. So:
1- How to predict for the future? Is creating a model based on for example 1995 to 2015 and predicting based on 2015 information suffice? (and then maybe predicting based on the result of 2015 prediction). Is this type of stepwise prediction the only way?
2- Is there any research paper you could suggest that predicts landuse change for distant future using machine learning techniques?
thanks.
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Hello,
Geoprospective is a difficult discipline to manipulate, not because it deals with the future, but because humans are like the Nature they are from : unpredictable. So, there is a possible solution : using together the nomothetic (spatial analysis) which explains us what is permanent through time (and so, we can suppose it will still be the case in 50 or 100 years from now) but also axiology which deals with ethics, esthetic but also (that's a personnal opinion) with cognitive science. Axiology is not permanent, even if scientific methods were tried on it, ethics change through time and between societies, esthetic too and i don't talk even talk of minds (the cultural matter) ! ... The mixing of those two sides should produce something interesting, as long as there is a perfect logical, reasoning and objective work.
See you here or there.
Térence
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In statistics, Cramér's V is a measure of association between two nominal variables, giving a value between 0 and 1 (inclusive). It was first proposed by Harald Cramér (1946).
It is actually considered in many papers I came accross that a threshold value of 0.15 (sometimes even 0.1) can be considered as meaningful, hence giving hints of a low association between the variables being tested. Do you have any reference, mathematical foundation or explanation on why this threshold is relevant ?
Regards,
Roland.
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Hello Roland,
There are guidelines, of course, but these may well be useless for many variable sets or contexts. I don't know of any mathematical reason to suggest that .15 (ir any other value) is magically better as a threshold for a relationship being judged as noteworthy.
Jacob Cohen, in his 1988 text, Statistical power analysis for the behavioral sciences (2nd ed.), proposed these levels for the simpler version of V, the phi coefficient (in which one of the two dimensions has 1 df):
"Small" effect size = phi of .10; "medium" ES = phi of .30; "large" ES = phi of .50.
However, Cohen would be the first to admit that such guidelines may be meaningless in specific data/variable/population contexts; there is no substitute for intimate understanding of these features.
Here's a simple example of how a very low correlation can still be useful: Consider a correlation of .01 between a no-cost, one-question cancer screener and the subsequent occurrence of cancer within a year. Sounds useless, right?
(With these hypothetical values from 100,000 cases: screen+/cancer+ = 6,472; screen+/cancer- = 57,922; screen-/cancer+ = 3,356; screen-/cancer- = 32,250; the chi-square = 10.114, and phi = .01). In this scenario, the one-question screener would potentially save nearly 6,500 lives. So, is it useful?
Good luck with your work.
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I have done LULC classification using LANDSAT images for my study area which includes a part of coastal seashore. The classification was done using 2 methods: the conventional supervised MLC method and spectral indices based classification. In both the cases it is found that intermixing of built-up, barren and coastal shore classes. Coastal shore appeared to be built-up class and barren to be again built-up class. Though it is claimed by many of the researchers that spectral indices based classification gave good overall accuracy and Kappa coefficient, the problem mentioned above still persist. It is observed in my current work that overall accuracy and kappa coefficient were enhanced to an extent. But, the problem of intermixing of pixels is more prevalent especially in coastal area.
Please let me know if you have any idea on how to tackle this issue.
Thank You.
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Dear when you perform classification, it is already give you the full thematic map and add to that thematic map for each class
regards
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(specifically into the mountain area)
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Interesting insights on the matter may be provided by the ESPON SUPER project (Sustainable Urbanisation and Land Use in European Regions).
The inception report is published already, and the interim report should follow in a month or so.
Hope this helps!
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I am studying about Remote Sensing, especially the application of remote sensing in land use land cover classification. I have a little bit of experience in python programing and am looking for a good resource for learning Python for image classification of various image data. Can anyone give me such a good resource, please? Thanks in advance.
Best regards,
Duong.
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Hi Phan Cao,
I think that ENVI (Environment for Visualizing Imagery) has a low entry level which allows you to get to image classification fast. The algorithms are state-of-the art for many applications including land use and land cover classification in supervised and unsupervised classification modes.
Hence have a look at the follwinf site to know more about this software, which I have been using for years now in remote sensing applications. It can also include Interactive Diagramming Language (IDL) when you need to program very specific appliations.
Here is the website of ENVI:
Lots of success,
Frank
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I have tried TerrSet but it didn't work properly, as It mainly works on urban sprawl. and my study area is free from anthropogenic activities like construction.
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Hello! I refer to DINAMICA EGO, which is developed here at the research center where I work. Any help with DINAMICA, I am available!
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Hi, My study covers 1981 to 2018. I need to classify Landsat images of 1981, 1991, 2001, 2011, 2018 to get land cover. I can do accuracy assessment of 2018 classification by ground truth points. but how can i measure the accuracy of 2001 or 1991 year images?
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Dear
THis is fairly common problem in LULC mapping. It is always possible to validate a recent map, since the land cover/land use can be checked for accuracy through field visit. However, for past LULC maps, all you can do is to use the maximum trusted data source you might have at your disposal which can be checked against your past remotely sensed maps. It can either be aerial photographs, reference LULC maps, ancillary data.
A common approach people often use is sampling from Google Earth satellite images. They are free but you cannot download them, but rather just browse them. However, since Google is providing a timeline feature for free, aiming at your area of interest, you can freely access old picture and sample data for each class of interest. Lots of published papers use this approach for validation when ancillary sources/aerial photographs or reference datasets for the past years are not available, yet it has proven to be a realiable method (see http://adsabs.harvard.edu/abs/2015SPIE.9644E..1NR and ). I can direct you to a tutorial here (https://ibis.geog.ubc.ca/courses/geob373/labs/IGETT_Exercises/google_earth_for_ground_truthing.html).
Also find attached to this answer the FAO Map Accuracy Assessment and Area Estimation practical guide advocating the same method for sampling data from Google Earth for map validation, along with formulas and a link to an interesting plugin developed to this end, CollectEarth (http://www.openforis.org/tools/collect-earth.html).
Hope this helps.
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It can be lumped to a catchment level (with average rainfall and % of land cover types e.g. forest, agriculture, urban) or raster cell based. I agree that, there are many other factors such as topography, soil type, evaporation/evapotranspiration, distance to reach as well as daily/event rainfall distribution that influences the river discharge. But at the moment, the purpose is to compare the net change in river discharge (or runoff) in relation to change in rainfall and/or land use land cover only without needing to specify other information.
I tried the Soil curve number method using land cover and hydrologic soil group, but found it not suitable for monthly or annual data as the response for various amount of rainfall differ a lot and it is aimed for event level runoff estimation.
Thanks a lot for the help
Dinesh
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if you search in the literature you will find many examples of lumped models based on stepwise multiple regression that include rainfall , landuse, evapotranspiration etc. I published a paper (sometime ago) Rainfall-Runoff Relationship and Water Budget for Zarqa River Basin I will add the full text to my profile ... hope that help
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Dear Researchers,
I have calibrated and validated my swat project for a particular Landuse rasyer data set.
Now, I want to develop Landuse change Scenarios in this swat project.
Plz guide me.
Kind Regards
Naveed
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Hi Naveed Ahmed. I normally analyze LU change scenarios as follows. First I calibrate and validate SWAT with the current LU scenario or whatever your baseline scenario is. Next I will re-run the model but modifying the LU input raster according with the scenarios of interest, and using the calibrated parameters that you came up with during the Calibration process. This approach implies that you create your scenarios of interest out of the model according with the problem that you want to analyze. One simple example would be analyzing a deforestation risk map you may identify future scenarios. SWAT also allows you to analyze BMP inside the model.
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Dear friends and colleagues,
our land use maps, which they include five land use classes, have been developed for three time periods. Now, the question is that, are we allowed to use non-parametric test in that case where we just have the area for these land-use classes in three years without repetition?
I wonder if you let me know what action should I take in this regards.
Sincerely yours
Bagher 
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I also agreed with Gustavo Alckmin
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Dear Researchers,
I have created the soil user file and now working of LULC file. I have done almost all only remaining are following:
Townland and
Ruralland
Both belongs to urban landcover, so its code must come from Urban database and accordingly code ID will be assigned in the user define Land-use text file. AM I right?
Secondly, Desert, Dryland and Plaindryland I am still struggling how to replace them from the land cover closest category.
Could you please guide me how to fix these problems.
Thanks in anticipation.
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I have just learned Dyna_CLUE modeling to simulate the future land use maps. If someone having stock with it kindly contact me, i have prepare easy guidelines to learn it. There are few crucial steps which you can not learn from user manual. Thanks
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I would be thankful if you could send me the guidelines on my email (elaheza@yahoo.com)
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Hello
i want to perform CA Markov using IDRISI selva. but this annoying error always appears. does anybody know how can i fix this error?
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Hello!
Make sure all the input files present in the same project directory. If not place them into same folder.
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Hi all,
For those of you which had a previous experience with Idridsi TerrSet (from ClarkLabs), I am considering working with LCM (Land Change Modeler) to model land use change over a rural watershed of 40 sq km in the sahelian climate (west africa).
I am considering three different types of land uses. I have the strong belief that all the land uses are being changed under the influence of the same set of driving variables. Amongst them, I have cultivated areas, which are continiously increasing, based on land use demand, which is closely (I believe) related to climate and population size.
Say I have annual population census (or density) values, as well as cumulative annual rainfall values over the whole simulation period. However, these values does not change spatially over the whole area,. They are rather constant in space, but time varying.
How can I input them in the modelling process, using a Multilayer Perceptron (MLP) ?
Roland.
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Dear Prof Gil Mahe,
Much thanks for the recommendation. I actually know well that paper, as well as the previous developpement made by Pierre Diello in his thesis work (2007) on Nakambe basin.
I actually got some interesting insights and ideas from this. However, in this work, we are highly interested in the mapping, modelling and forecasting of spatial distribution of LULC changes, we went in a different direction, that is LULC modelling.
Ultimately, the problem has been "solved". I believe I might share the approach we used in another writeup, hopefully soon.
Thanks again.
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This project is looking for soil organic carbon data and changes in China.
We are seeking your support in collecting SOC data to predict and map SOC. What we would need are the SOC, bulk density, and soil texture contents for entire China or any provinces or any district in China.
Any metadata in more detail are welcomed.
Thanks in advance.
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The 10th IALE World Congress will take place July 1st-5th 2019 in Milan, featuring the theme of "Nature and society facing the Anthropocene challenges and perspectives for landscape ecology". http://www.iale2019.unimib.it/
Have a look at our symposia SYMP4 Reconstructing the past landscapes to simulate future sustainable scenarios through multidisciplinary approaches
We accept abstracts by 25th of February!!
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Grazie Claudia per l'invito che terrò presente.
Paolo
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i have 20 raster with 5 class and want to calculate transition matrix for my Agent-based model
I prefer using R
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Hi Aydin,
I recommend this tutorial to quantify Landcover's changes in space and time and the use of markov chains: http://benbestphd.com/landscape-ecology-labs/lab2.html
Also, for this purpose you can use the lulcc package : https://spiral.imperial.ac.uk/bitstream/10044/1/41199/3/gmd-8-3215-2015.pdf
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As part of my research, I am modelling runoff discharge on a rural watershed. I would like to activate Land Use Update with SWAT. I am using ArcGIS 10.3.1 with ArcSWAT, along with SWATCUP 5.1.6 for automatic calibration. I used SWAT LUU tool (see https://saraswat-swat.rcac.purdue.edu/swatluu) to prepare inputs lup.dat and relevant files for 3 differents land use scenerios (2004, 2009 and 2017). My simulation goes from 2004 to 2017, with one year warm up (2004).
I noticed that when I run SWAT-CUP, it seems to find lup.dat, since deleting any of the associated *.dat files containing HRU fractions (HRU_FR) values returns an error. However, during the auto-calibration process, *.hru files are constantly edited, but their HRU_FR (first line) does not change. As such, it seems that land use update does not work.
Are there any recommended guidelines or anything I have missed ? In case any information is needed upon this, I would be glad to provided them. Thanks in advance.
Roland.
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Hi Roland,
Do you mean that the SWAT_CUP copys the lup.dat but It does not copy the associated files (HRUs fraction files)?
If this is the case, might be you could try to copy the land use change fraction files to the working folder of SWAT_CUP for it.
About the .hru changing constantly but the HRU fraction does not change. I think this is because every time the parameters was change, all of the file will be rewrite by SWAT_CUP. SWAT_CUP does not need to change the HRU_FR in .hru file because SWAT will change it according to the information in the lup.dat file.
I also create an R script to generate input files (TxtInOut) for SWAT (new HRUs emerings due to land use change will also be consider and you can also interpolated you HRU fraction at any time). If you interest in using this script, please let me know.
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Hello there,
I want to see the effect of LULC change on rainfall over the Indian region. So, want to know how we can replace the default urban LULC with crop land LULC in WRF. Please some one suggest me how to do that in WRF? Presently I am using MODIS data.
Regards
Jitendra
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Yes, they are the grid locations based on the [row range, column range] of the NetCDF file instead of their 'latitude and longitude' or x, y position as shown in GrADS. Thanks, the problem is solved.
Thanks.
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Can anyone please help me to find some research papers related to 'solving land use conflicts of an agricultural farm'?
Thank you.
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Where to find free or cheap very high resolution multispactral imagery and LIDAR for the entire world ?
Also, repositories of historical imagery/maps would be very useful.
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Thank you for your answer Dr Salem,
Kind regards
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Most land (38.6%) modified by humans for agriculture (pasture + croplands) is about 19.4 million square miles. Another 14.9% (about 7.7 million square miles) is land that is modified for other uses (logging, mines, planted forests, erosion, urban areas). If the urban areas constitute about the 3% of these 7.5 mill. square miles then 58.275 Ha is the land occupied by urban areas in the world. How could I estimate the number of hectares that are used in urban agriculture in the world? Would FAO have this information? Where?
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Hi Massimo and Kenneth,
Thank you for answering/commenting my question. The 58.275Ha are inclusive of roads, buildings, parking lots, shopping malls and similar infrastructure. From my score here above I would like to figure out the actual number of Ha. that are cultivated within urban areas. Thanks!
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I have a series of land use maps at different times as a result of a classification process on Landsat images. I am mapping 3 different thematic classes : bare soils, vegetation and croplands.
I would like to answer the following : are the trends of differents land use classes significant ? I believe chi-square test might help here.
How should I run the test, step by step ? should i sample some pixels ? how much ? or work with the entire rasters ? Can anyone explain or at least point me to relevant lectures ?
Thanks.
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Roland,
I see no reason why Chi-squared test cannot be used. The data you wish to collect is nominal data. The problem is the sampling procedure that would suit best for extracting your data. Do you apply systematic or random sampling. That depends largely on the nature of the spatial patterns present on the maps. Probably a method of random sampling would be preferable.
Certainly relate land use/types specific to similar time sets. Once data has been gathered and tabulated for running the Chi test, set up your null hypothesis, I.e. that there is NO relationship between . . . While composite tests can be done, I think testing pair by pair is better. Composite testing can obscure the main relationship.
Having said that, I am not sure but that other graphic and/or statistical methods may prove more useful, e.g. trend graphs or histograms. They require more interpretation than Chi values but can give much more useful information, especially concerning changes over time.
George
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Dear Experts,
I am going to estimate land surface temperature in a cloudy city and prepare its LST map for further analysis. I searched among Landsat images of the case study , but, the cloud coverage is very high ! (Since I prefer to use high resolution images, i searched among Landsat images).
I would be thankful if you provide me some solutions and suggestions.
Best regards,
Majid
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I want to relate field measured TSS and reflectance to come up with a regression model to estimate sediment yield.
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Dear you need to convert DN to radiance then convert the radiance to reflectance by using Band math tool
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I want to understand how transitional probabilities are calculated for land use change modelling, given four (4) state land use types for a previous period (T1) and a new period (T2) spanning ten years.  
Please, using the above percentages how do I derive the transitional probabilities for the two periods. Make the answer simple.
Thanks for your assistance.
Sam
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See my answer to your personal message. Also look at the excel example there and on the previous answer above. Note you have to have the SOLVER ADD-IN activated in EXCEL. The idea is to have an objective (like minimize costs) and constraints.
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I am working on a research proposal on the issue of agricultural expansion, intensification and deforestation in tropical Latin America. I am particularly interested in looking not only at socio-economic and technological drivers, but also institutional ones. In particular, which aspects of governance are important in preventing further spatial expansion of agriculture in tropical Latin America? How do different land tenure systems affect the process? What is the role of indigenous communities? So far I have been thinking of looking at the dry Chaco in Northern Argentina and perhaps another case in Ecuador (in order to perform a comparative analysis). I would very much appreciate collaborations with local institutions/researchers.
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Dear all,
I am looking for a kind member of the Society for Historical Archaeology who could nominate my PhD dissertation to the 2018 Kathleen Kirk Gilmore Dissertation Award, please.
This work is about late-Holocene human occupations and disturbances in Central Africa, their impact on tropical forests and the disruption on land use caused by the European colonization. The manuscript is written in English. It has been well received by the jury (in Belgium) as a outstanding multidisciplinary contribution, at the crossroads between archaeology and ecology.
Please find the text in attachment to have a look on it, and do not hesitate to recommend this post or to forward the question to anybody who could be interested in it.
Thank you so much for your help.
Best regards,
Julie Morin-Rivat
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Je suis plus phytosociologue mais je vous recommande l ouvrage de Hachid M. ''Aux sources de l Afrique 50 siècles avant les pyramides
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Hello Everyone,
I want to use VIC model for permafrost regions to simulate runoff under changing climatic and vegetation cover. Any guide / information may be very supportive and helpful for me. So please share if you have any kind of support / guide /help etc.
Regards
Naveed
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Interested
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For my study on soil carbon content under different land uses in the Peruvian Amazon I am measuring bulk density. Mainly in the upper 10 cm from primary and secondary forest there are considerable amount of roots above 2x2 mm. I am correcting for stones by assuming stones to have a bulk density of 2.6 g/cm-3, but I have not been able to find literature on how to correct for roots?
I assume (dry) roots are somehow lighter than the soil they substitute, so in order to not underestimate BD of the forests, I need a conversion rate - although roots are naturally present here?
I am not measuring root biomass in my study.
Thanks in advance for your time!
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Dear Tine, as the roots are mostly water - when you dry the sample (to measure the total dry weight) you will have removed most of the mass associated with the roots anyway. When you have collected the samples (ie from a fixed volume) and you are preparing them for drying, you could try to remove the larger roots without taking any attached soil - this may not be easy or possible if the soil has a lot of clay in it. The error of including fine roots is likely to be less than that of the actual sampling method (particularly the errors associated with compaction when driving cores into the ground or the trimming of samples once removed). I would like to follow up on a comment from Gerben. It is worth calculating the density of the fine earth fraction (ie the density of the soil between stones as this gives you an idea of the relative density that roots experience (ie related to mechanical impedance) if you are comparing sites with and with out stones - of layers with different stone content. This may not strictly be the "bulk" density of the overall soil, but it is important information depending on your reason for measuring it is. If you are measuring bulk density to convert carbon content of mass/mass basis to mass/area basis, then you will need to know the volume of fine fraction (whole sample minus stone volume) to be able to calculate the mass/area.
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I am currently researching the emission variations between agricultural land and energy crop cultivation. There is extensive literature about the argument of preserving agricultural land for food production and keeping energy crop production separate. This is primarily due to the increasing demand of food and decreasing available land for such agriculture.
My research has led me to the understanding that there are additional carbon emissions that need to be accounted for when calculating the environmental impacts of energy crops. This is due to previously stored carbon in the soils of uncultivated land, such as grassland, which is released once cultivation begins.
Is anyone working on or know of a study that has extensively calculated the emissions of both separate land uses and/or the variations between the same piece of land being used for agriculture and then converted into energy crops?
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As part of a research work, I am modelling Land Use/Land cover changes over the span of 4 decades on a 40 km² watershed in a rural area located in sahelian climate (west africa). I am mainly interested in three types of land units, namely bare soils, cultivated soils and vegetated areas. I have been able to map them accurately enough using remote sensing analysis of Landsat 5 TM/Landsat 8 OLI Images. As such, I now have land cover maps for the watershed at four dates, 1985, 1995, 2007 and 2017. I am now looking into modelling the changes using a set of driving factors (yet to be identified) and assess land cover changes. I ran into land use simulation models mostly based on Cellular Automaton (CA) concepts such as Land Use Sim (http://www.landusesim.com/landusesim-land-use-modeling-simulation-software/) but it seems to be a paid software. Are there any other free simulation software/packages one can point me at ? Preferably, something that can be easily tight to a GIS environnment (ESRI ArcGIS for example) for easier raster/vector processing.
Thanks in advance.
Roland.
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There are several LUCC models for free. One quite widespread and famous is Dinamica Ego (http://csr.ufmg.br/dinamica/). You also have the CLUE model (http://www.ivm.vu.nl/en/Organisation/departments/spatial-analysis-decision-support/Clue/index.aspx) developed by a research team in Netherlands.
Also in this paper ( An open and extensible framework for spatially explicit land use change modelling: The lulcc R package) you can find the presentation of a R package which includes two LUCC models, being CLUE one of them if I am remember well.
For a general overview, you have short presentations of several LUCC models in the last part of this book: http://www.springer.com/us/book/9783319608006
I have given you above the links to some of them. However, I am sure there are another ones different which are also for free.
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in rapid urban expansion, peri-urban area's landscape (forest, hill area, wetlands) are occurred to change by uncontrolled land-use, impact on buffering settings. how to measure and make further policies to overcome?
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I would like to meet any researcher/expert in this area from a German University of Research Institution?
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Dear HYBAM scientific team,
My name is Fabian Santos, I am from Ecuador and currently I am doing a Ph.D. at the University of Bonn. Since data from my country is not easy to collect, I am wondering if you have a publication which summarizes the results of HYBAM project for the Napo Watershed, as my research is analysing its land cover/land use change during the last 40 years.
I will be pleased and thankful for your information as I didn't find any scientific publication of your results and this certainly, do not benefit knowledge transferability.
Thanks for your attention.
Best regards,
Fabián
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Thanks very much for the feedback!
Best regards,
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Landscape history of Dehesa Montado.
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Currently we are working on dehesa in Andalusia (see attached). Further, for your consideration a somewhat older article from dehesa in Extremadura and the most recent historical overview I have come across.
Evidently, we are interest in your experience with P. cinnamomi in dehesa or otherwise in oak, if any.
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Can anyone recommend any advantages and disadvantages:
1) agent-based models;
2) artificial neural networks;
3) cellular automata;
4) economics-based models; and
5) Markov chains;
for land use change modelling?
Any sugestions, references?
Thank you!
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Hi there. The following is my opinion, references mostly from memory, caveat emptor!
1) agent-based models;
hard to calibrate, especially if there are many agents, not always spatially explicit. Probably better for understanding the process of change rather than creating future simulations, especially if the main goal is to understand the interaction of the agents of change. But recent work is beginning to address these limitations, e.g. see the CRAFTY model (Murray-Rust et al)
2) artificial neural networks;
rules of transition are calculated by the neural network and are invisible to the user - the model is effectively a "black box", these models have a tendency to overfit to the calibration date. On the other hand, they do produce good simulations by standard goodness-of-fit measures. See Pijanowski and collaborators, from 2005 (Grand Traverse Bay Watershed Michigan and numerous other cases up to the present day)
3) cellular automata;
most practical examples rely on trial and error calibration, rather than empirical evidence of association between land use and drivers. But transition rules are transparent (unlike ANN) since the user must explicitly define them. The modeller achieves a fuller understanding of the change processes and they perform well on pattern-based or cell-by-cell statistical measures. Convincingly model the dynamics of urban growth. See work by Keith Clarke and collaborators (1997, 1998 etc), White and Engelen 1993, White et al 1997 (city of Cincinnati). See also work on automatic or semi-automatic calibration of these models - Straatman, B., White, R., & Engelen, G. (2004). Towards an automatic calibration procedure for constrained cellular automata. Computers, Environment and Urban Systems, 28(1), 149-170, and also more recent work (see esp. Barreira-Gonzalez et al 2015, and Norte Pinto and Pais Antunes 2010)
4) economics-based models; and
a range of econometric models exist that claim to reliably associate the size of cities with three key drivers, distance from central business district, agricultural land value, and population. Problem is that this strong association at small spatial scales (e.g. all US cities) breaks down at large spatial scales (e.g within an individual region). Also does not really explain the process or pattern of change. See Brueckner and Fansler 1984, etc etc also critique by Bockstael and Irwin 1999
We talked about some of these issues in a recent working paper, maybe its of interest.
5) Markov chains;
Don't know, I've not looked into these in detail.
Hope this helps!
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What satellite images are the best for studying land-use changes in urban areas and why? Some free sources would be great, thanks.
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Combination of optical data along with High incidence angle like polarized RADAR data acquired during summer season is probably the best data for Urban studies. Please go through one of my research publications using the link provided with the answer:
Comparative evaluation of potential of optical and SAR data for the detection of human settlements using digital classification (2006),
HS Srivastava, P Patel, Y Sharma, RR Navalgund - International Journal of Geoinformatics, Vol. 02, No. 03, pp. 21-28.
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Can anyone advise how to do a sensitivity analysis on the effect of land use change on river flow regimes? I want to find out which parameter/factor is contributing more effect to stream flow. The parameters are land use activities, i.e. cropped land, woodland, bare land, residential, water bodies and grassland. I only have information on streamflow and percentage land cover for each activity for different periods from 1980.
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hello , I want to calculate the potential of different land use on co2 sequestration in my case study, but i cant find a citable paper that show me how much co2 sink in soil, forest and other land use generally. thanks for your help  
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Hi Maryam, you can get enough information about your question by reading the following article:
Effects of Land-Use Change on the Carbon Balance of Terrestrial Ecosystems
R.A. Houghton
Good Luck!
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Generally speaking, specifics about the individual chemical cocktails used in a project are considered proprietary, and are usually only available with explicit permission from the data owner (the company doing the job). Some exceptions for example, would be data collected from IHS (usually comes at a cost), or data voluntarily promulgated (e.g. fracfocus.org). If you are looking for general soil/ water data, I would start here:
I would then peruse similar pubs like this one:
 then continue mining data from the subsources therein (i.e. the Acknowledgements). Hope that helps.
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The inventory for the CBM-CFS3 (carbon balance model from the canadian forest sector) requires volume-age curves for each stand and I cannot figure out how to obtain these curves.
I can find information about dbh, aboveground biomass and volume but I cannot find how this relates to age. Can anyone tell me what I am missing here? I am specifically looking at mexican oaks (Quercus castanea, Q. crassifolia, Q. laeta, Q. obtusata y Q. rugosa). 
The model developers, Kurz et al. (2009) state: "Forest management agencies and industry have built up large libraries of yield tables to describe the accumulation of volume in the merchantable portion of tree stems as a function of stand age. To enable the use of these data sources, CBM-CFS2 was modified from using biomass over age to CBM-CFS3, that uses merchantable volume over age data to simulate growth."
Where can I find these tables with volume-age tables?
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Here it the large file document
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If anyone have recent data of  land use change status of Nepal available please post for me ?
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Hy Deepa, you can download the land use change from Global Forest Change (Hansen, et atl)at 2000-2014. there is deribated form Landsat (30 m) and iots veru good for a country or region.
This is the link:
Best regards
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I am looking to analyse how a change in land use in a catchment will effect peak discharge for the floods in Carlisle 2015. What model would be suitable and what data would be needed to do this?
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I think that could be interesting a distributed hydrological model to capture/modeling soil change effect at catchment scale. My research group developed this free model based on DEM approach. WiMMed (Watershed Integrated Model for Mediterranean Environments) is a physically-based, distributed hydrological model, developed by the Environmental Flows Dynamics Research Group (University of Granada) and the Fluvial Dynamics and Hydrology Research Group (University of Córdoba) for the Andalusian Regional Government (Junta de Andalucía). You have this info from http://www.ugr.es/~herrero/ 
Distributed data of soil for landuses in raster format is important to assess these differences. 
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Hi, 
Could anyone can provide me some materials or guidelines that allow me to understand how to develop a new stage-damage function for flood event. 
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Maybe even this thesis may be interesting (urban flooding)
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Currently I am conducting a research on land use change and conservation of plant biodiversity in peri-urban  Kajulu Hill, within Kisumu City Kenya. However during data collection I did find out that within the study area there is a cultural centre established in early 90s by the National government of Kenya, in my interaction with the staff it seems very little has been done with regards to intergation of culture in environmental conservation in the region.
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Thank you soo very much for your contributions, I am organizing a session with officials from the cultural center to see how we can chat the way forward to promote environmental conservation through culture.
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Hi.
I have developed an index of suitability for a specified land use activity based on a spatial multi criteria analysis approach (continuous raster dataset with values 0-255); additionally, we have empirical data showing where this activity presently occurs and the intensity at which it occurs (present use) (also normalised continuous raster 0-255). The assumption is that this virtual space has not yet been fully exploited, either spatially or in terms of intensity, for this activity. Given this assumption, the problem is how to statistically describe the agreement (or lack of) between the empirical (present use) and predicted suitability datasets? This seems identical to an invasive species habitat modelling problem, where comprehensive presence and absence data may not available (where a habitat has not yet been fully exploited) to evaluate model output (false presences/absences (?)) - any ideas how I could deal with this in my example?
Thanks in advance for any advice.
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Hi Craig, you have to evaluate predicted land use suitability versus empirical data, can take the diffrences about de hectares or kilometers and calculate the accuracy in %.
Regards
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anybody
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Use Land Change Modeler (LCM) to assess land use and cover change. You can find this model in IDRISI Selva. Good luck. 
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